Enterprises are increasingly capturing, storing, and mining a plethora of information related to communications with their customers. Often this information is stored and indexed within databases. Once the information is indexed, queries are developed on an as-needed basis to mine the information from the database for a variety of organizational goals.
The enterprise data can originate from a myriad of sources and even external feeds, but ultimately the goal for the enterprise is that all the data be consolidated, indexed, and related within a central enterprise data warehouse.
Over a few short years of gathering all this data, an enterprise can quickly realize that they have overwhelmed the existing storage capacity of their database. As a result, the enterprise may attempt to expand the storage, which in many cases can substantially slow the response times of the database. In other cases, the enterprise may try to upgrade to another database; but, this approach is even more problematic because a significant data port has to occur to make the existing data in the existing database compatible in the new database architecture.
In fact, most database architectures utilizes a homogeneous hardware architecture with respect to storage interconnects and storage devices. This may work well when most of the data being stored in the database maintains an equal weight in terms of importance to an enterprise and all the data has roughly the same performance throughput requirements.
However, in the ever evolving technology marketplace, data is acquired in a variety of different formats (video, image, text, audio, graphics, etc.) and available nearly instantaneously over the World-Wide Web (WWW). An enterprise typically also finds that some data needs to be more secure and accessed more readily than other types of data and that some data is frequently accessed but rarely changed. So, a stagnant and one-size fits all approach is no longer practicable for any competitive enterprise.